General Criminality as a Marker of Heterogeneity in Domestically Violent Men: Differences in Trauma History, Psychopathology, Neurocognitive Functioning, and Psychophysiology
Bibliographic record
Abstract
This study examined whether involvement in general criminal behavior was a useful marker of critical historic, psychological, and cognitive aspects of heterogeneity in domestically violent men. Two subgroups of domestically violent men, those with ( n = 56) and without ( n = 54) a history of criminal involvement, were compared with a group of nonviolent men ( n = 82) on internalizing psychopathology, substance abuse, maltreatment in the family of origin, cognitive and executive functioning, and psychophysiological factors. Results found that domestically violent criminal men scored higher than the other two groups on a number of measures including history of childhood violence exposure, childhood externalizing behavior, and adult internalizing psychopathology. No differences were found on their psychophysiological reactivity and cognitive performance. The domestically violent noncriminal group and the comparison group were largely similar on study variables with the exception of education and substance use. Results suggest that general theories of antisocial behavior may be relevant and helpful for understanding domestically violent and criminally involved batterers, whereas social and family violence theories may be of greater relevance to noncriminally involved batterers. Implications of these results for intervention are considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".